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Validation of a new image analysis procedure for quantifying filamentous bacteria in activated sludge.
Liwarska-Bizukojc, Ewa; Bizukojc, Marcin; Andrzejczak, Olga.
Affiliation
  • Liwarska-Bizukojc E; Lodz University of Technology, Institute of Fermentation Technology and Microbiology, ul. Wolczanska 171/173, 90-924 Lodz, Poland E-mail: ewa.liwarska-bizukojc@p.lodz.pl.
  • Bizukojc M; Lodz University of Technology, Department of Bioprocess Engineering, Wolczanska 213, 90-924 Lodz, Poland.
  • Andrzejczak O; Lodz University of Technology, Institute of Fermentation Technology and Microbiology, ul. Wolczanska 171/173, 90-924 Lodz, Poland E-mail: ewa.liwarska-bizukojc@p.lodz.pl.
Water Sci Technol ; 70(6): 955-63, 2014.
Article in En | MEDLINE | ID: mdl-25259482
ABSTRACT
Quantification of filamentous bacteria in activated sludge systems can be made by manual counting under a microscope or by the application of various automated image analysis procedures. The latter has been significantly developed in the last two decades. In this work a new method based upon automated image analysis techniques was elaborated and presented. It consisted of three stages (a) Neisser staining, (b) grabbing of microscopic images, and (c) digital image processing and analysis. This automated image analysis procedure possessed the features of novelty. It simultaneously delivered data about aggregates and filaments in an individual calculation routine, which is seldom met in the procedures described in the literature so far. What is more important, the macroprogram performing image processing and calculation of morphological parameters was written in the same software which was used for grabbing of images. Previously published procedures required using two different types of software, one for image grabbing and another one for image processing and analysis. Application of this new procedure for the quantification of filamentous bacteria in the full-scale as well as laboratory activated sludge systems proved that it was simple, fast and delivered reliable results.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Sewage / Bacteria / Image Processing, Computer-Assisted / Software / Microscopy Language: En Journal: Water Sci Technol Journal subject: SAUDE AMBIENTAL / TOXICOLOGIA Year: 2014 Type: Article

Full text: 1 Database: MEDLINE Main subject: Sewage / Bacteria / Image Processing, Computer-Assisted / Software / Microscopy Language: En Journal: Water Sci Technol Journal subject: SAUDE AMBIENTAL / TOXICOLOGIA Year: 2014 Type: Article